1. Field of the Invention
The invention generally relates to sensor systems, and more particularly to systems and methods of attaining data fusion from sensor suites onboard ballistic projectiles.
2. Description of the Related Art
Within this application several publications are referenced by Arabic numerals within brackets. Full citations for these and other publications may be found at the end of the specification immediately preceding the claims. The disclosures of all these publications in their entireties are hereby expressly incorporated by reference into the present application for the purposes of indicating the background of the invention and illustrating the general state of the art.
For application to small/medium caliber, air bursting munitions, for which neither Global Positioning System (GPS) based location sensors nor height-above-ground (HOB) proximity sensors are practical, there is an acute need for both an accurate range-sensing fuze during direct fire use, and for an accurate altitude-sensing fuze during large-target-range barrage use. This need arises from the sensitive dependence of lethality upon the range and altitude errors in burst point location for the direct fire and barrage cases, respectively. Conventional fuzing methodology use a computed nominal trajectory simulation, based upon nominal initial/Met (meteorological) conditions, to determine either a time-to-target or a turns-count-to-target value which is communicated to the projectile before firing. The onboard sensor, timer or turns-counter, merely serves as a gauge as to when this value has been reached by the projectile. The breadth of non-trivial range-error sources and altitude-error sources makes it difficult, however, to obtain highly accurate range or altitude predictions using only a single fuze sensor, such as a timer or an ambient electric/magnetic field sensor to count turns of the spin-stabilized projectile.
In exterior ballistics the trajectory of a projectile is defined to be a complete prescription of its rigid body motion (six degrees of freedom) as a function of time starting at gun exit. Three of the degrees of freedom determine the projectile's center-of-mass momentum vector and the other three determine the projectile's angular momentum vector about the center-of-mass. As the projectile's mass and moment of inertia are presumed known, this is equivalent to knowing the combined histories of its velocity vector and angular velocity (spin) vector. Assuming that the gun's location and the projectile's initial orientation are known, the center-of-mass position vector and orientation for the projectile for subsequent times can hence also be deduced. The in-flight prediction of all or part of this information, or information derived thereof, is a problem of paramount importance for military applications. The synthesis of such information from the output of one or more sensors onboard the projectile constitutes trajectory self-sensing, or onboard ballistic navigation.
One of the uses of trajectory sensing is as a feedback to an active guidance control system for correcting the flight path of the projectile so that it accurately reaches its target destination. In the absence of an active guidance control capability, onboard ballistic navigation can still be utilized for either fuze-sensing or the (inverse) problem of inferring projectile aerodynamic coefficients from (field test) sensor output data. The term “fuze-sensing” is meant to convey unguided projectile trajectory self-sensing for the specialized purpose of gauging the attainment of a targeted trajectory condition by the projectile during its flight, the attainment of which signals projectile detonation. This targeted condition is usually chosen so as to maximize the lethality of the detonation. Impact delay and point detonation are the two contact-sensing fuze modes, which do not require knowledge of the projectile's trajectory. Excluding these modes, trajectory self-sensing further specializes to the role of air burst fuze-sensing. Air burst fuze-sensing, in turn, can be further subdivided into direct fire and indirect fire applications, the direct fire case typically being that of nearly straight trajectories with small gun elevations.
Airburst lethality for targets under direct fire is much more sensitive to range error than it is to either altitude or deflection error. It is hence more optimal with respect to lethality to sense range as a target condition than it is to sense either altitude or deflection. Sensors currently used for air burst range sensing can be divided into two classes. In the first class sensors directly probe their environment by sending/receiving signals (typically RF signals), as in the case of proximity sensors, or they receive man-made signals from known, “friendly” sources such as GPS satellites. Active sensors are included in this class. Sensor suites from this class usually have the advantages of direct measurement of projectile (relative or absolute) position and high accuracy. However, these sensors do have their disadvantages as well including that the dependence of these sensors upon external signals means that they are susceptible to jamming, hence a backup fuze-sensing system is advisable. Also, clutter (such as tree canopies) can reduce the reliability of proximity sensors or hinder projectile tracking.
In addition, small volume, shape-conformity, low unit cost, gun ruggedness (high acceleration tolerance), and low power consumption constraints on the onboard sensors and their associated electronics severely limit the options available for in-flight trajectory sensing, and hence range-sensing in particular. The severity of these constraints grows dramatically with the inverse of the caliber of the munition(s), the smallest caliber munitions having the most severe constraints. These constraints tend to preclude the use of sensors from this first class in many small/medium caliber munitions. On the other hand, passive sensors, such as accelerometers and turn counters (for spin stabilized munitions) do not suffer from these deficiencies. However, trajectory information must be indirectly inferred from their output.
Numerous factors determine the trajectory path that a particular projectile takes for a given round within a particular occasion. For example, parameter values representing the projectile's inherent aerodynamic/mechanical response (mass, moments of inertia, various drag coefficients, etc.) influence the trajectory. They arise from the projectile's geometry, design, manufacturing process, and the influence of its immediate environment during its flight. Met (meteorological) data such as air pressure, air temperature, wind velocity humidity, and possibly their local spatial distributions (down-range data) hence also determine the particular trajectory taken. Finally, initial condition data such as gun location, quadrant elevation, gun azimuth, muzzle exit velocity magnitude, and initial spin rate altogether affect the trajectory as well. These latter two are related by:
      initial  spin  rate  (Hz)    =      c    ⁢                  ⁢                  muzzle  exit  velocity  magnitude  (m/s)                    barrel twist  (cal/rev)            where
  c  =                    1000        ⁢                                  ⁢                  (                      mm            ⁢                          /                        ⁢            m                    )                            caliber        ⁢                                  ⁢        of        ⁢                                  ⁢        munition        ⁢                                  ⁢                  (                      mm            ⁢                          /                        ⁢            cal                    )                      .  
Target data, such as slant range to target and target elevation are used to determine quadrant elevation and possibly gun azimuth, and hence can be considered as pre-conditional to the initial condition data. Two common trajectory simulation models[2,3] with wide usage are the full 6-dof (degree of freedom) model and the 4-dof modified point mass (MPM) model.
However, three of the biggest causes of differences between trajectory predictions for a given model and actual test flight trajectories arise from (1) the lack of accurate, flight-test-corrected aerodynamic data in the model; (2) inaccuracy/uncertainty of Met/initial-condition data in the model; and (3) the limitations of the model itself. For a given occasion, a fire control computer will measure/sense as much of the baseline information as is practical for that particular gun system, so that some of the pre-flight-determined components of the projectile's flight are known to within various error measurement tolerances. The fire control computer will presume/estimate the remaining pre-flight baseline data and the downrange data that it needs in order to compute a unique nominal (baseline) trajectory that, by definition, passes through both the targeted range and targeted altitude simultaneously for that occasion. It may also correct the gun azimuth of the nominal trajectory for wind, predicted drift (end-of-flight deflection), etc. as well. If the fire control computer were omnipotent then there would be no computational errors, so that the actual trajectory taken by the projectile would match that of the computed nominal trajectory. Moreover, ballistic navigation would then be deterministic, so that there would be no need for sensors onboard the projectile. Unfortunately, the actual trajectory taken by the projectile differs from the computed nominal trajectory mainly due to differences between the measured projectile flight and the actual projectile flight.
Furthermore, conventional range sensing methods are generally based upon the use of the pre-flight-computed nominal trajectory and the in-flight measurement of a “gauge variable” in order to determine when the targeted range value has been attained by the projectile. A gauge variable is a variable that quantitatively gauges the progress of a projectile along all, or some portion of, its trajectory path. As an example, if a given trajectory is divided into two pieces at the point of maximum altitude then the pre-maximum altitude constitutes a separate gauge variable from the post-maximum altitude. Time itself is the most obvious and basic global gauge variable. In fact, the conventional passive range sensing methods consists of an onboard timer gauging the attainment of a predetermined time-to-target value (estimated from the nominal trajectory).
Conventional methods of range sensing generally monitor agreement between the evolving, in-flight-measured value of a gauge variable and that fixed value of the gauge variable corresponding to the targeted range value, as computed from the nominal trajectory. When agreement is indicated, a “fire” signal is generated to initiate detonation. The main difference between these methods is in the choice of the gauge variable. However, a problem that may occur with conventional approaches is that the nominal trajectory, upon which they depend, may be significantly in error due to the accumulated effect of numerous error sources. Efforts to correct this, for example, currently consist of singling out one of the major sources of error, such as the statistical variations in muzzle exit velocity magnitude, and minimizing its effects.
Conventional range sensing methods can be mathematically expressed as follows: for timing, θ*=t*, where θ* is the target gauge value and t is the time variable with t=0 at the gun exit. For turns counting, θ*=TC*, where TC is the turns count starting from TC=0 at the gun exit. For corrected timing, θ*=(Vnom/Vactual)t*, Vnom is the nominal muzzle exit velocity magnitude, Vactual is the actual (measured) muzzle exit velocity magnitude, and t* is the time-to-target for ordinary (uncorrected) timing. For time-turns hybrid, θ*=TC* if Rtarget is in the supersonic portion of the nominal trajectory, where Rtarget is the target range. If Rtarget is in the subsonic portion of the nominal trajectory, then one measures θ=TC until θ=TCM=1, at which point θ resets to θ=δt (the measured elapsed time from the transition at θ=TCM=1) until reaching the final target value θ*=δt*=t*−tM=1, where TCM=1 and tM=1 are the turns count and time, respectively, at Mach one (M=1) and where t* is the time-to-target-range (all three as determined by the nominal trajectory). The pre-flight computed values for TCM=1 and δt* would be passed to the projectile. For a 1D accelerometer, θ*=(∫∫accel)*, where ∫∫accel is the twice time-integrated value of the acceleration component along the projectile's major axis, the corresponding muzzle exit velocity component from the nominal trajectory being used as one of the constants of integration, wherein it is assumed that the accelerometer is at the projectile's center-of-gravity. With these range sensing methods, the onboard sensor generally acts as a gauge of θ values with the onboard signal processor acting as a sentinel waiting for the value θ=θ* to be attained.
One of the concepts of fuze-sensing is that of deciding in-flight from sensor readings when the projectile has attained a condition of maximum lethality with respect to its detonation location. This is approximately achieved by monitoring the progression of the value of a particular gauge variable so as to determine when this value has attained a pre-established value. The particular gauge variable used for this purpose, denoted here as θlethal, is chosen so as to approximately maximize lethality sensitivity with respect to perturbations (errors) in θlethal about an optimal detonation value of [θlethal]target, which is pre-established by targeting data. Practically, θlethal could represent range, altitude, or perhaps something more sophisticated. Unfortunately, there is usually no single sensor, which can directly measure the value of θlethal. To remedy this, the conventional practice is to instead monitor the progress of another gauge variable, denoted here as θsensor, whose value can be measured directly (or with reasonable signal processing) from sensor output. Given sufficient targeting data, a value for [θlethal]target is pre-computed, a nominal trajectory is determined, and the value:
[θsensor]target=nominal trajectory value θsensor at which θlethal=[θlethal]target is then pre-computed and passed to the projectile. The fuze subsequently determines when the condition:[θsensor]measured=[θsensor]target has been attained during flight. As previously indicated, the problem with this standard practice is that when the above condition is actually attained one usually has a significant, nonzero error:|θlethal−[θlethal]target|>0due to the difference between the nominal (pre-computed) trajectory and the actual trajectory taken by the projectile. A common strategy to remedy this is to choose θsensor so as to be insensitive to the largest source of error for θlethal.
Ultimately, there are two main issues pertaining to range sensing accuracy that are not addressed by any of these methods individually. First, not only are there many error sources leading to a significant cumulative range error, but a significant number of them are each individually significant contributors to range error. Second, sensing a gauge variable merely to detect a target value is a waste of valuable information, and using onboard resources merely as a sentinel is a waste of computing potential. In fact, the significant increases in computing power and decreases in unit cost and size that have occurred in digital signal processors (DSP) and central processing units (CPU) have vastly increased in-flight computing potential. This potential has largely been unexploited in conventional range sensing strategies. Therefore, due to the limitations of the conventional systems and methods, there is a need for a novel projectile trajectory tracking methodology, which overcomes the above-identified deficiencies of the conventional methods.